采用人工智能技术的自动设计综合

F.J Vico , F.J Veredas , J.M Bravo , J Almaraz
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引用次数: 30

摘要

在工业设计领域,设计综合是一项非常复杂的任务。自动化的主要困难是设计和性能空间的定义,以一种计算机可以生成最佳解决方案的方式。与已经提出的机器学习和基于知识的方法不同,我们的方法将设计综合视为优化问题。从这个角度来看,神经网络和遗传算法可以用来实现适应度函数和实现优化设计所需的搜索方法。该方法已在电话机设计中得到验证。尽管该应用程序的目标是基于美学和人体工程学线索(主观信息),但该算法成功地收敛到良好的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic design synthesis with artificial intelligence techniques

Design synthesis represents a highly complex task in the field of industrial design. The main difficulty in automating it is the definition of the design and performance spaces, in a way that a computer can generate optimum solutions. Following a different line from the machine learning, and knowledge-based methods that have been proposed, our approach considers design synthesis as an optimization problem. From this outlook, neural networks and genetic algorithms can be used to implement the fitness function and the search method needed to achieve optimum design. The proposed method has been tested in designing a telephone handset. Although the objective of this application is based on esthetic and ergonomic cues (subjective information), the algorithm successfully converges to good solutions.

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